Triple
T1411603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dow Jones U.S. Auto Manufacturers Index |
E31816
|
entity |
| Predicate | tracksSector |
P26630
|
FINISHED |
| Object | consumer discretionary sector |
—
|
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: consumer discretionary sector | Statement: [Dow Jones U.S. Auto Manufacturers Index, tracksSector, consumer discretionary sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tracksSector Context triple: [Dow Jones U.S. Auto Manufacturers Index, tracksSector, consumer discretionary sector]
-
A.
track
Indicates that one entity follows, monitors, or keeps a record of another entity’s state, behavior, or progress over time.
-
B.
frontSector
Indicates that one entity is located in the forward-facing sector or region relative to another entity.
-
C.
trackGauge
Indicates the distance between the inner faces of the rails in a railway track system.
-
D.
crossesSectionOf
Indicates that one entity passes through or over a specific segment or portion of another entity.
-
E.
trackRecordUsedFor
Indicates that a track record is utilized as a basis or input for some subsequent decision, evaluation, or process.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3e1da988190bc7c187e193539b6 |
completed | March 1, 2026, 10:55 p.m. |
| PD | Predicate disambiguation | batch_69a4bf048b648190ab77d9b45cb4855f |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf8158ac8190b8360ecccc2980bc |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:59 p.m.