Triple
T2382363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucille |
E46337
|
entity |
| Predicate | scaleLength |
P266
|
FINISHED |
| Object | 24.75 inches (typical Gibson scale) |
—
|
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: 24.75 inches (typical Gibson scale) | Statement: [Lucille, scaleLength, 24.75 inches (typical Gibson scale)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scaleLength Context triple: [Lucille, scaleLength, 24.75 inches (typical Gibson scale)]
-
A.
magnitudeScale
Indicates the scale or measurement system used to quantify the magnitude or intensity of something.
-
B.
areaScale
Indicates a proportional relationship where one area value is a scaled (enlarged or reduced) version of another by a specific factor.
-
C.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
D.
properLengthMeasuredIn
Indicates that the proper (intrinsic or rest-frame) length of an entity is expressed using a specified unit of measurement.
-
E.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7b98c988190abdb4fe51bf65bde |
completed | March 7, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69abc59f73f08190924a36d7d475d8f4 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.