Triple
T20661303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rage |
E507764
|
entity |
| Predicate | hasPublisherImprint |
P2763
|
FINISHED |
| Object | Signet |
—
|
NE NERFINISHED |
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: Signet | Statement: [Rage, hasPublisherImprint, Signet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Signet Context triple: [Rage, hasPublisherImprint, Signet]
-
A.
Signet
chosen
Signet is a mass-market paperback imprint known for publishing popular fiction and genre titles.
-
B.
Argyle Enterprises
Argyle Enterprises is a film production company best known for its involvement in classic mid-20th-century cinema, including the 1963 horror film "The Haunting."
-
C.
Golden Company
The Golden Company is a famously disciplined and formidable sellsword company in Essos, renowned for its loyalty to its contracts and its origins among exiled Westerosi nobles.
-
D.
Britannia Industries
Britannia Industries is one of India’s leading food companies, best known for its wide range of biscuits, dairy products, and bakery items sold under popular household brands.
-
E.
Wyman-Gordon
Wyman-Gordon is an industrial manufacturer known for producing high-strength forged components, particularly for the aerospace and energy industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f16adc8190b2b9a69586fa7444 |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:44 a.m.