Triple
T25736447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fitz JCR |
E645388
|
entity |
| Predicate | typicalOfficers |
P194736
|
FINISHED |
| Object | President |
—
|
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: President | Statement: [Fitz JCR, typicalOfficers, President]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOfficers Context triple: [Fitz JCR, typicalOfficers, President]
-
A.
officersAre
Indicates that certain individuals hold the role or position of officers within a specified group, organization, or context.
-
B.
officersServeAs
Indicates that certain individuals hold and perform the role or duties of officers within a particular organization or context.
-
C.
officersKnownAs
Indicates that certain officers are referred to or recognized by a particular name or designation.
-
D.
officersServeIn
Indicates that certain officers perform their duties or hold positions within a specified organization, unit, or jurisdiction.
-
E.
officersHave
Indicates that certain individuals hold official positions or roles within a specified organization or entity.
- 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_69e77e85254081908d79ee4e8715f283 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd864235b481908738dbb69556bc62 |
completed | May 8, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_69fd8373b6bc819091c554f29ee17fec |
completed | May 8, 2026, 6:32 a.m. |
| PDg | Predicate description generation | batch_69fd8640e1d4819081c98f15eeb221ab |
completed | May 8, 2026, 6:44 a.m. |
Created at: April 21, 2026, 11:27 p.m.