Triple
T26135998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MER |
E659384
|
entity |
| Predicate | issuerHeadquartersAddressCity |
P165843
|
FINISHED |
| Object | New York City |
—
|
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: New York City | Statement: [MER, issuerHeadquartersAddressCity, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: issuerHeadquartersAddressCity Context triple: [MER, issuerHeadquartersAddressCity, New York City]
-
A.
issuerFormerHeadquartersCity
Indicates the city where the issuer’s former headquarters were located before moving or changing.
-
B.
sponsorHeadquartersCity
Indicates the city where the sponsoring organization’s main headquarters is located.
-
C.
headquartersLocation
Indicates the place where an organization’s main administrative center or principal office is located.
-
D.
employerHeadquarters
Indicates the location where an employer’s main corporate offices or central administrative operations are based.
-
E.
laterCompanyHeadquartersCity
Indicates that the specified city is the location of a company’s headquarters during a later period in time, following an earlier headquarters location.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65a9cb0bc8190bf8a9b319900bad5 |
completed | May 2, 2026, 8:12 p.m. |
Created at: April 26, 2026, 8:17 p.m.