Triple
T15265523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conflent |
E364891
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Olette
Olette is a small historic village in the Conflent region of the French Pyrenees, known for its traditional stone architecture and scenic mountain setting.
|
E1147492
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Olette | Statement: [Conflent, containsTown, Olette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olette Context triple: [Conflent, containsTown, Olette]
-
A.
Olta
Olta is a small town in the La Rioja Province of northwestern Argentina that serves as an administrative and service center for the surrounding rural region.
-
B.
Ojakkala
Ojakkala is a village in the municipality of Vihti in southern Finland, known for its rural residential character and proximity to the Helsinki metropolitan area.
-
C.
Ollon
Ollon is a municipality in the canton of Vaud in southwestern Switzerland, known for its vineyards and proximity to the Alpine resort area of Villars.
-
D.
Ota
Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
-
E.
Ota
Ōta is a large ward in southern Tokyo, Japan, known for Haneda Airport, residential neighborhoods, and a mix of industrial and commercial areas.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Olette Triple: [Conflent, containsTown, Olette]
Generated description
Olette is a small historic village in the Conflent region of the French Pyrenees, known for its traditional stone architecture and scenic mountain setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Olette Target entity description: Olette is a small historic village in the Conflent region of the French Pyrenees, known for its traditional stone architecture and scenic mountain setting.
-
A.
Olta
Olta is a small town in the La Rioja Province of northwestern Argentina that serves as an administrative and service center for the surrounding rural region.
-
B.
Ojakkala
Ojakkala is a village in the municipality of Vihti in southern Finland, known for its rural residential character and proximity to the Helsinki metropolitan area.
-
C.
Ollon
Ollon is a municipality in the canton of Vaud in southwestern Switzerland, known for its vineyards and proximity to the Alpine resort area of Villars.
-
D.
Ota
Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
-
E.
Ota
Ōta is a large ward in southern Tokyo, Japan, known for Haneda Airport, residential neighborhoods, and a mix of industrial and commercial areas.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00851c5b88190a296b6a105d3ee30 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee600340c8190a1888d35c2c1bc86 |
completed | May 9, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69fee714cf6c81908dc4427590eeae85 |
completed | May 9, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feeae4731081909964bd8b1ea3dd7a |
completed | May 9, 2026, 8:05 a.m. |
Created at: April 10, 2026, 3:14 a.m.