Triple
T18956682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messier 32 |
E463797
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | M32 |
—
|
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: M32 | Statement: [Messier 32, alsoKnownAs, M32]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M32 Context triple: [Messier 32, alsoKnownAs, M32]
-
A.
M32
chosen
M32 is a compact dwarf elliptical galaxy that orbits the Andromeda Galaxy within the Local Group.
-
B.
M32R
M32R is a 32-bit RISC microprocessor architecture developed by Mitsubishi (later Renesas) for embedded systems and low-power applications.
-
C.
M-32
M-32 is an east–west state trunkline highway in northern Michigan that connects several inland communities across the northern Lower Peninsula.
-
D.
M3
M3 is a circular line of the Copenhagen Metro that loops around the city center, connecting key districts and interchange stations.
-
E.
M3
M3 is one of the main lines of the Bucharest Metro rapid transit system, serving key residential and commercial areas of Romania’s capital.
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d5cdf2d08190a0aecd3fa5335a75 |
completed | April 20, 2026, 7:29 a.m. |
Created at: April 10, 2026, noon