Triple
T7817851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Tompkins |
E181055
|
entity |
| Predicate | Daniel D. Tompkins |
P79174
|
FINISHED |
| Object | was Governor of New York |
—
|
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: was Governor of New York | Statement: [Fort Tompkins, Daniel D. Tompkins, was Governor of New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Daniel D. Tompkins Context triple: [Fort Tompkins, Daniel D. Tompkins, was Governor of New York]
-
A.
secondPresident
Indicates that the subject is the second person to hold the office of president of the specified entity or organization.
-
B.
thirdPresident
Indicates that the subject holds the position of being the third president in a specified ordered sequence of presidents.
-
C.
penultimatePresidentOf
Indicates that the subject served as the second-to-last president of the object (such as a country or organization).
-
D.
firstElectedPresident
Indicates that the subject became the first person ever elected to the office of president of the specified entity or organization.
-
E.
Cornelius Ennis
Indicates a relationship or association involving the entity or name “Cornelius Ennis,” such as authorship, attribution, or participation in an event or context.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf9708bdc8190a5154efe0f96f458 |
completed | March 30, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:40 p.m.