Triple
T14011584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benguet |
E337091
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Tublay
Tublay is a rural municipality in the province of Benguet in the Cordillera region of the Philippines, known for its mountainous terrain and cool climate.
|
E1073030
|
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: Tublay | Statement: [Benguet, contains, Tublay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tublay Context triple: [Benguet, contains, Tublay]
-
A.
Tuburan
Tuburan is a coastal municipality in the province of Cebu in the Philippines, known for its natural springs and rural landscapes.
-
B.
Tutuyan
Tutuyan is a town in North Sulawesi, Indonesia, serving as the administrative and political center of East Bolaang Mongondow Regency.
-
C.
Tübatulabal
Tübatulabal is a Native American people and their Uto-Aztecan language traditionally associated with the Kern River region of California.
-
D.
Taybad
Taybad is a city in northeastern Iran near the Afghan border, known as a local commercial and transit hub within Razavi Khorasan Province.
-
E.
Tahla
Tahla is a small town in northern Morocco, situated in the Rif region and known as a gateway to nearby mountain landscapes.
- 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: Tublay Triple: [Benguet, contains, Tublay]
Generated description
Tublay is a rural municipality in the province of Benguet in the Cordillera region of the Philippines, known for its mountainous terrain and cool climate.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tublay Target entity description: Tublay is a rural municipality in the province of Benguet in the Cordillera region of the Philippines, known for its mountainous terrain and cool climate.
-
A.
Tuburan
Tuburan is a coastal municipality in the province of Cebu in the Philippines, known for its natural springs and rural landscapes.
-
B.
Tutuyan
Tutuyan is a town in North Sulawesi, Indonesia, serving as the administrative and political center of East Bolaang Mongondow Regency.
-
C.
Tübatulabal
Tübatulabal is a Native American people and their Uto-Aztecan language traditionally associated with the Kern River region of California.
-
D.
Taybad
Taybad is a city in northeastern Iran near the Afghan border, known as a local commercial and transit hub within Razavi Khorasan Province.
-
E.
Tahla
Tahla is a small town in northern Morocco, situated in the Rif region and known as a gateway to nearby mountain landscapes.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed5cfd0819085b9c860b119a9de |
completed | April 14, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbacaa16e88190995fd86951fb54e6 |
completed | May 6, 2026, 9:03 p.m. |
| NEDg | Description generation | batch_69fbada0a2408190b77d163aee17400e |
completed | May 6, 2026, 9:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbaeeeb594819087b57da166495a72 |
completed | May 6, 2026, 9:13 p.m. |
Created at: April 9, 2026, 10:19 p.m.