Triple
T4603536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devil Without a Cause |
E100374
|
entity |
| Predicate | copiesShippedInUS |
P57388
|
FINISHED |
| Object | 11000000 |
—
|
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: 11000000 | Statement: [Devil Without a Cause, copiesShippedInUS, 11000000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: copiesShippedInUS Context triple: [Devil Without a Cause, copiesShippedInUS, 11000000]
-
A.
hasShip
Indicates that one entity possesses, owns, or is equipped with a ship.
-
B.
sentShipsTo
Indicates that one entity dispatched or directed ships to another entity or location.
-
C.
supportsPackageShipments
Indicates that one entity provides the capability or service needed to handle and transport package shipments for another entity.
-
D.
stateShip
Indicates that a ship is officially registered, documented, or associated with a particular state or governmental authority.
-
E.
supportsNonDocumentShipments
Indicates that the carrier or service is able to handle and transport shipments that consist of non-document items (e.g., goods, merchandise, or parcels).
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5975ec688190839bd22669343a76 |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522c811c81909aae4feadae33174 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:11 p.m.