Triple
T34869863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Behar Colony |
E1005717
|
entity |
| Predicate | nearestMajorPortCity |
P38207
|
FINISHED |
| Object | Karachi |
—
|
NE NERFINISHED |
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: Karachi | Statement: [Behar Colony, nearestMajorPortCity, Karachi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestMajorPortCity Context triple: [Behar Colony, nearestMajorPortCity, Karachi]
-
A.
nearestMajorPort
chosen
Indicates the closest significant seaport to a given location or entity, typically based on geographic distance.
-
B.
nearestMajorCity
Indicates that one city is the closest significant urban center to another location or city compared to all other major cities.
-
C.
nearbyCityOrPort
Indicates that one location is geographically close to a city or port, typically within a short travel distance.
-
D.
nearestIslandCity
Indicates that one city is the closest city located on an island relative to a given reference location or city.
-
E.
majorCityNearMouth
Indicates that a major city is located close to the mouth (outflow point) of a river.
- F. None of above.
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_69f76dbde1c08190a24e7f9beb564c8d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.