Triple
T17416541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stand in the Schoolhouse Door |
E423503
|
entity |
| Predicate | officeHeldByActor |
P127364
|
FINISHED |
| Object | Governor of Alabama |
—
|
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: Governor of Alabama | Statement: [Stand in the Schoolhouse Door, officeHeldByActor, Governor of Alabama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldByActor Context triple: [Stand in the Schoolhouse Door, officeHeldByActor, Governor of Alabama]
-
A.
officeHeldOf
Indicates that a specific office or position is (or was) held by a particular person or entity.
-
B.
officeHeldByMember
Indicates that a specific office or position is held or occupied by a particular member.
-
C.
officeHeldDuring
Indicates that a person occupied a specific official position during a particular time period.
-
D.
officeHeldUnder
Indicates that one entity holds or has held an official position, role, or office under the authority, jurisdiction, or administration of another entity.
-
E.
aboutOfficeHeld
Indicates that one entity is related to, or provides information about, a specific office or position that is or was held by another 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44232ecdc8190ac8958c1780fea19 |
completed | April 19, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
| PDg | Predicate description generation | batch_69e3b2a33e8481908fa6ef45290d08aa |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:46 a.m.