Triple
T1795660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago bureau chief of The New York Times |
E39596
|
entity |
| Predicate | hasSeniorityLevel |
P2393
|
FINISHED |
| Object | senior editor |
—
|
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: senior editor | Statement: [Chicago bureau chief of The New York Times, hasSeniorityLevel, senior editor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeniorityLevel Context triple: [Chicago bureau chief of The New York Times, hasSeniorityLevel, senior editor]
-
A.
hasSeniorNCO
Indicates that an entity has, is assigned, or is associated with a senior non-commissioned officer in a supervisory or leadership capacity.
-
B.
seniorRank
Indicates that one entity holds a higher or more senior rank or position than another entity.
-
C.
eligibilityLevel
Indicates the degree or tier of qualification an entity has for a given benefit, service, or status.
-
D.
hasLevel
chosen
Indicates that an entity possesses or is associated with a particular degree, rank, or stage within an ordered scale or hierarchy.
-
E.
hasRankAtRetirement
Indicates the rank or position an entity held at the time it retired or was formally withdrawn from active service.
- F. None of above.
Provenance (3 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_69a88632aa588190ba3978fde0db5bbd |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab61b6ea188190aab9fb839bf1e367 |
completed | March 6, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69aa61d2f7a8819090301f92d3e358c7 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.