Triple
T28188334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KamLAND experiment |
E716234
|
entity |
| Predicate | madeLandmarkMeasurement |
P66282
|
FINISHED |
| Object | precision measurement of Δm²21 |
—
|
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: precision measurement of Δm²21 | Statement: [KamLAND experiment, madeLandmarkMeasurement, precision measurement of Δm²21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: madeLandmarkMeasurement Context triple: [KamLAND experiment, madeLandmarkMeasurement, precision measurement of Δm²21]
-
A.
measuredBy
Indicates that something’s quantity, extent, or value is determined or expressed using a particular measurement method, instrument, or unit.
-
B.
isLandmarkFor
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
C.
performedMeasurement
chosen
Indicates that an entity has carried out a specific measurement activity on another entity or phenomenon.
-
D.
hasMeasurement
Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
-
E.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
- 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f64288631881909ffef7aa84199ae8 |
completed | May 2, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 10:24 p.m.