Triple
T1096066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M2 beam line |
E24273
|
entity |
| Predicate | beamLineNumber |
P11728
|
FINISHED |
| Object | M2 |
—
|
LITERAL 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: M2 | Statement: [M2 beam line, beamLineNumber, M2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beamLineNumber Context triple: [M2 beam line, beamLineNumber, M2]
-
A.
hasLineNumber
chosen
Indicates that something is associated with a specific line number, typically denoting its position within an ordered sequence such as lines of text or code.
-
B.
beamLine
Indicates a relationship where one entity directs or projects a beam or focused line (such as light, energy, or signal) toward another entity.
-
C.
usesLineCode
Indicates that one entity employs or references a specific line code as part of its operation, identification, or communication.
-
D.
beam
Indicates that one entity emits, directs, or projects a concentrated line or stream (such as light, energy, or information) toward another entity.
-
E.
formerLineName
Indicates that the object is a previous or former name by which the referenced line was known.
- F. None of above.
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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99ffb3481908cd168b6c58e1c6d |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b7448c148190a3c9a4158ebd05b4 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.