Triple
T36578105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guzara District |
E902311
|
entity |
| Predicate | hasMajorUrbanCenterNearby |
P112043
|
FINISHED |
| Object | Herat city |
E66483
|
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: Herat city | Statement: [Guzara District, hasMajorUrbanCenterNearby, Herat city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorUrbanCenterNearby Context triple: [Guzara District, hasMajorUrbanCenterNearby, Herat city]
-
A.
hasNearbyMajorCityCountry
Indicates that an entity has a nearby major city located in the specified country.
-
B.
nearestLargeUrbanArea
chosen
Indicates that one entity is the closest major city or large urban center to the other entity.
-
C.
hasMajorCity
Indicates that a location possesses at least one city of significant size, importance, or influence within its region or country.
-
D.
majorCityNearMouth
Indicates that a major city is located close to the mouth (outflow point) of a river.
-
E.
connectsToUrbanCenter
Indicates that one entity has a direct or functional linkage to an urban center, such as through infrastructure, services, or regular interaction.
- F. None of above.
Provenance (4 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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0346b487088190814e4bd0765cb609 |
completed | May 12, 2026, 3:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3d178366808190b0363a997318a30d |
completed | June 25, 2026, 11:56 a.m. |
| PD | Predicate disambiguation | batch_6a0346428c60819090e5ea815c0921ca |
completed | May 12, 2026, 3:24 p.m. |
Created at: May 3, 2026, 4:11 p.m.