Triple
T19831256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hercules Globular Cluster |
E476465
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | M13 |
—
|
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: M13 | Statement: [Hercules Globular Cluster, alsoKnownAs, M13]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M13 Context triple: [Hercules Globular Cluster, alsoKnownAs, M13]
-
A.
M-13
M-13 is a state highway in Michigan that runs through the Saginaw Bay region, connecting communities such as Essexville with the broader state road network.
-
B.
M 13
chosen
M 13 is a globular star cluster in the constellation Hercules and one of the brightest and best-known such clusters in the northern sky.
-
C.
M-131
M-131 is a regional road in the Community of Madrid, Spain, that provides access to and from the town of Torrelaguna.
-
D.
M-33
M-33 is a regional road in Montenegro that forms part of the country’s main inland transport network.
-
E.
M-33
M-33 is a state trunkline highway in Michigan that runs through the northern part of the Lower Peninsula, serving rural communities and connecting to several major routes.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656ce68b48190aa25b29d0b6ea021 |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.