Triple
T894274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas |
E19307
|
entity |
| Predicate | volumeNumberingIn |
P5040
|
FINISHED |
| Object | 1–4 U.S. (Dallas) in United States Reports |
—
|
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: 1–4 U.S. (Dallas) in United States Reports | Statement: [Dallas, volumeNumberingIn, 1–4 U.S. (Dallas) in United States Reports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: volumeNumberingIn Context triple: [Dallas, volumeNumberingIn, 1–4 U.S. (Dallas) in United States Reports]
-
A.
seriesVolumeNumber
chosen
Indicates the specific volume number assigned to an item within an ordered series.
-
B.
verseNumber
Indicates the specific numbered position of a verse within an ordered sequence, such as in a chapter, song, or poem.
-
C.
volume
Indicates the amount of three-dimensional space an entity occupies or contains.
-
D.
numberOfVolumes
Indicates the total count of separate volumes or parts that make up a multi-volume work or collection.
-
E.
editionNumber
Indicates the specific sequential number assigned to an edition of a work within its series of published versions.
- 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad22b6fc819093e655c8ce1f738b |
completed | March 1, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69a4aa94f7c881908deeb62308942e19 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.