Triple
T178993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Press Secretary |
E3641
|
entity |
| Predicate | typicallyHoldsRank |
P7007
|
FINISHED |
| Object | Assistant to the 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: Assistant to the President | Statement: [Press Secretary, typicallyHoldsRank, Assistant to the President]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyHoldsRank Context triple: [Press Secretary, typicallyHoldsRank, Assistant to the President]
-
A.
militaryRank
Indicates that one entity holds a specific position or level within a hierarchical military ranking system relative to another entity.
-
B.
honorificRank
Indicates that one entity holds a formal title or honorific status in relation to another entity.
-
C.
hasLiturgicalRank
Indicates that an entity is assigned a specific status or level within a liturgical or religious ceremonial hierarchy.
-
D.
highestRankIn
Indicates that one entity holds the top or most senior rank within a specified group, category, or context relative to other entities.
-
E.
rankedAs
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25900709c8190a65e778936be5dd5 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566b53d481909c0ed40dd3719e8c |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2582b7f648190b0ef676b8bdc1c65 |
completed | Feb. 28, 2026, 2:51 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.