Triple
T487379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Office of Government Information Services |
E9907
|
entity |
| Predicate | contactPoint |
P5347
|
FINISHED |
| Object | FOIA requesters |
—
|
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: FOIA requesters | Statement: [Office of Government Information Services, contactPoint, FOIA requesters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contactPoint Context triple: [Office of Government Information Services, contactPoint, FOIA requesters]
-
A.
appointmentMethod
Indicates how an appointment is arranged, such as the channel, process, or means used to schedule it.
-
B.
associatedNumber
Indicates a relationship where a specific number is linked or assigned to an entity as its associated value.
-
C.
interactionPoint
chosen
Indicates a specific location or moment where two or more entities come into contact or engage with each other.
-
D.
officeNumber
Indicates the specific room or suite number assigned to an office within a building or complex.
-
E.
address
Indicates that one entity directs spoken or written communication specifically to 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0de66308190a18503a482881cfc |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf63fbc819090ea6ca11f39116a |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.