Triple
T89565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Mets |
E1799
|
entity |
| Predicate | homeCitySince |
P3872
|
FINISHED |
| Object | 1962 |
—
|
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: 1962 | Statement: [New York Mets, homeCitySince, 1962]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeCitySince Context triple: [New York Mets, homeCitySince, 1962]
-
A.
city1
Indicates that the subject is classified as a city.
-
B.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
-
C.
placeOfBirth
Indicates the location where a person or other entity was born.
-
D.
cityOfOriginal
Indicates the city from which something or someone originally comes or was first created or established.
-
E.
servesAsFocusCityFor
Indicates that a city functions as a primary or designated focus city for an airline, organization, or transportation network, typically hosting significant but not hub-level operations or activities.
- 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_69a24d1a97dc819094e6c021fe9b05a7 |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24feef1b08190bb9525f71cce053e |
completed | Feb. 28, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69a24eb82d408190b0f9c786152e8e4c |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a24fed6b8c819080a6c0cd3b16e6bd |
completed | Feb. 28, 2026, 2:16 a.m. |
Created at: Feb. 28, 2026, 2:07 a.m.