Triple
T1185396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonsay |
E25233
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Kiloran
Kiloran is a small coastal settlement on the Scottish island of Colonsay, known for its scenic bay and sandy beach.
|
E145974
|
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: Kiloran | Statement: [Colonsay, hasSettlement, Kiloran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiloran Context triple: [Colonsay, hasSettlement, Kiloran]
-
A.
Nicholaston
Nicholaston is a small coastal village on Wales’s scenic Gower Peninsula, known for its proximity to dunes, woodlands, and the popular Nicholaston Burrows and beach.
-
B.
Tynaarlo
Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
-
C.
Loralai
Loralai is a town and district in northern Balochistan, Pakistan, known historically as a regional administrative and trade center.
-
D.
Mauregard
Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
-
E.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
- 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: Kiloran Triple: [Colonsay, hasSettlement, Kiloran]
Generated description
Kiloran is a small coastal settlement on the Scottish island of Colonsay, known for its scenic bay and sandy beach.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kiloran Target entity description: Kiloran is a small coastal settlement on the Scottish island of Colonsay, known for its scenic bay and sandy beach.
-
A.
Nicholaston
Nicholaston is a small coastal village on Wales’s scenic Gower Peninsula, known for its proximity to dunes, woodlands, and the popular Nicholaston Burrows and beach.
-
B.
Tynaarlo
Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
-
C.
Loralai
Loralai is a town and district in northern Balochistan, Pakistan, known historically as a regional administrative and trade center.
-
D.
Mauregard
Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
-
E.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd39245881908766c41943dc2752 |
completed | March 1, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aca2e7d28c8190acf5ae2237e6d4e0 |
completed | March 7, 2026, 10:12 p.m. |
| NEDg | Description generation | batch_69aca3752a3c81908bd6d9744ad5f5a2 |
completed | March 7, 2026, 10:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69aca3e44bf481908c5726adddc4b428 |
completed | March 7, 2026, 10:17 p.m. |
Created at: March 1, 2026, 7:45 p.m.