Triple
T8708253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galactic Center series |
E206705
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Furious Gulf |
E206708
|
NE 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: Furious Gulf | Statement: [Galactic Center series, hasPart, Furious Gulf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Furious Gulf Context triple: [Galactic Center series, hasPart, Furious Gulf]
-
A.
Furious Gulf
chosen
Furious Gulf is a hard science fiction novel by Gregory Benford, part of his Galactic Center series exploring humanity’s struggle against machine intelligences in a far-future universe.
-
B.
Bone Gulf
Bone Gulf is a coastal gulf in Indonesia that forms part of the coastline of South Sulawesi.
-
C.
El Golfo
El Golfo is a small coastal village on Lanzarote in the Canary Islands, famous for its striking green lagoon set in a volcanic crater beside black-sand beaches.
-
D.
Gulf Wind
Gulf Wind was a named passenger train that provided long-distance service in the southeastern United States for the Louisville and Nashville Railroad.
-
E.
GULF
GULF is a network of presidents and top leaders from leading global universities that convenes under the World Economic Forum to address key issues in higher education and research.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58ffa6a481908866b6239d1d9b92 |
completed | March 31, 2026, 11:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28b78e90819098ab1d4877ab88fe |
completed | April 3, 2026, 2:40 a.m. |
Created at: March 30, 2026, 6:35 p.m.