Triple
T1250136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warren Commission |
E26854
|
entity |
| Predicate | appendicesCount |
P25806
|
FINISHED |
| Object | 26 volumes of hearings and exhibits |
—
|
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: 26 volumes of hearings and exhibits | Statement: [Warren Commission, appendicesCount, 26 volumes of hearings and exhibits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appendicesCount Context triple: [Warren Commission, appendicesCount, 26 volumes of hearings and exhibits]
-
A.
annexCount
Indicates the number of annexes or supplementary parts associated with a primary entity or document.
-
B.
appendixIIIContent
Indicates that the content pertains specifically to materials, items, or information listed in Appendix III of a referenced document or convention.
-
C.
appendixIIContent
Indicates that one entity is the content included in, or associated with, the second appendix of another entity.
-
D.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
E.
annex
Indicates the act of formally incorporating one entity, typically a territory, into the domain or control of another.
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf84c73c8190bbb14265cd7ab6ae |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6b075881908e867c25b5080e25 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:47 p.m.