Triple
T19291797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HR 1149 |
E482459
|
entity |
| Predicate | hasCompanion |
P22642
|
FINISHED |
| Object | Taygeta B |
—
|
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: Taygeta B | Statement: [HR 1149, hasCompanion, Taygeta B]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taygeta B Context triple: [HR 1149, hasCompanion, Taygeta B]
-
A.
Taygeta
chosen
Taygeta is one of the prominent stars in the Pleiades (Seven Sisters) open star cluster in the constellation Taurus.
-
B.
Cotyora
Cotyora was an ancient Greek city on the southern coast of the Black Sea in the region of Pontus, known as a colony of Sinope and a waypoint in Xenophon’s Anabasis.
-
C.
Bettega
Bettega is an Italian surname most notably associated with former Juventus and Italy footballer Roberto Bettega.
-
D.
Tector
Tector is a member of the 2nd Massachusetts Militia Regiment, a fictional military unit featured in the science fiction television series "Falling Skies."
-
E.
Tayshet
Tayshet is a town in Irkutsk Oblast, Russia, known as a major railway junction in Siberia.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc819a7881909a7afbd06d9dd3f0 |
completed | April 20, 2026, 10:14 a.m. |
Created at: April 10, 2026, 1:31 p.m.