Triple
T1384496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allahabad |
E29812
|
entity |
| Predicate | isMetropolitanCity |
P27229
|
FINISHED |
| Object | Yes |
—
|
LITERAL 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: Yes | Statement: [Allahabad, isMetropolitanCity, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMetropolitanCity Context triple: [Allahabad, isMetropolitanCity, Yes]
-
A.
isMetropolitanCoreOf
Indicates that one area functions as the central, most urbanized core within a larger metropolitan region or system.
-
B.
isMegacity
Indicates that a city has an extremely large population and urban area, typically qualifying it as a major global metropolitan center.
-
C.
isCoreCity
Indicates that a city serves as a primary, central, or most important urban area within a larger region, system, or network.
-
D.
isGlobalCity
Indicates that a city holds significant worldwide influence in areas such as economics, culture, politics, or connectivity, making it an important node in the global system.
-
E.
hasMetropolitan
Indicates that an entity is associated with, served by, or located within a specific metropolitan area.
- F. None of above. chosen
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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c33896548190b44f70c9aaaed9b6 |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0335f7081908d50046ced4cdee0 |
completed | March 1, 2026, 10:39 p.m. |
Created at: March 1, 2026, 7:59 p.m.