Triple
T11410237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chip Roy |
E270349
|
entity |
| Predicate | has served as |
P1827
|
FINISHED |
| Object | chief of staff to U.S. Senator Ted Cruz |
—
|
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: chief of staff to U.S. Senator Ted Cruz | Statement: [Chip Roy, has served as, chief of staff to U.S. Senator Ted Cruz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has served as Context triple: [Chip Roy, has served as, chief of staff to U.S. Senator Ted Cruz]
-
A.
servedAs
chosen
Indicates that one entity held and performed the role, position, or function associated with another entity for some period of time.
-
B.
servedInRole
Indicates that one entity performed duties or held a position within a specified role or office in relation to another entity.
-
C.
alsoServedAs
Indicates that an entity held an additional role or position beyond the primary one already mentioned.
-
D.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
E.
servedInOfficeTo
Indicates that one entity held and performed the duties of a particular office or position for the benefit or under the authority of another entity.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8015017d08190b4020c76545556d6 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.