Triple
T12606427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathia Gali |
E300989
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Ayubia |
E930491
|
NE FINISHED |
How this triple was built (2 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: Ayubia | Statement: [Nathia Gali, near, Ayubia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayubia Context triple: [Nathia Gali, near, Ayubia]
-
A.
Ayubia
chosen
Ayubia is a popular hill resort and national park area in Pakistan’s Galyat region, known for its cool climate, pine forests, and scenic chairlift.
-
B.
Labayu
Labayu was a 14th-century BCE Canaanite ruler known from the Amarna letters for his aggressive expansionism and conflicts with neighboring city-states.
-
C.
Ubaque
Ubaque is a municipality in central Colombia known for its rural Andean landscapes and traditional agricultural communities.
-
D.
Arjona
Arjona is a Spanish-origin surname shared by various notable individuals in fields such as entertainment, sports, and the arts.
-
E.
Gualba
Gualba is a small municipality in the Vallès Oriental comarca of Catalonia, Spain, known for its natural surroundings near the Montseny Massif.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e7f2dc8190a42cab7a0e5ea7f3 |
completed | April 10, 2026, 7:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f66869c0b08190b13bcebbe354cd98 |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:11 p.m.