Triple
T20327410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayer family |
E492375
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Caelum |
—
|
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: Caelum | Statement: [Bayer family, hasPart, Caelum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caelum Context triple: [Bayer family, hasPart, Caelum]
-
A.
Caelum
chosen
Caelum is a small, faint southern constellation introduced in the 18th century, representing a sculptor’s chisel.
-
B.
Caelestis
Caelestis is a Romanized form of the North African goddess Tanit, venerated as a celestial mother and protector deity in Carthaginian and later Roman religion.
-
C.
Gamma Caeli
Gamma Caeli is a relatively bright star in the small southern constellation Caelum, notable as one of its primary stellar members.
-
D.
Corulag
Corulag is a prominent planet in the Star Wars galaxy’s Core Worlds region, known for its Imperial military academies and strategic political significance.
-
E.
Kyela
Kyela is a town and district in southern Tanzania known for its fertile land, rice production, and location near the northern shores of Lake Nyasa.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e677e513608190b70527cd9f4d5da3 |
completed | April 20, 2026, 7 p.m. |
Created at: April 16, 2026, 11:21 a.m.