Triple
T19112928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assistant Secretary of the Army |
E467834
|
entity |
| Predicate | numberOfDistinctPositions |
P1029
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Assistant Secretary of the Army, numberOfDistinctPositions, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDistinctPositions Context triple: [Assistant Secretary of the Army, numberOfDistinctPositions, 5]
-
A.
numberOfPositions
chosen
Indicates the total count of distinct positions or roles associated with a given entity.
-
B.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
-
C.
numberOfMovements
Indicates the total count of distinct movements or motion events associated with the given entity or context.
-
D.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
numberOfPaths
Indicates the count of distinct paths or routes that exist between specified points or within a given structure.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e39553708190b64e24e1d190833e |
completed | April 20, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:05 p.m.