Triple
T24916375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HERA |
E623995
|
entity |
| Predicate | hadMajorDetector |
P136929
|
FINISHED |
| Object | H1 |
—
|
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: H1 | Statement: [HERA, hadMajorDetector, H1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMajorDetector Context triple: [HERA, hadMajorDetector, H1]
-
A.
hasMajor
Indicates that an entity (typically a person or student) has a specific primary field of academic study or specialization.
-
B.
mainDetector
chosen
Indicates that an entity serves as the primary or principal detector in relation to another entity or system.
-
C.
hadMajorFront
Indicates that an entity (such as a conflict or war) involved a significant primary front or theater of operations in a specified location or context.
-
D.
detected
Indicates that an entity has observed, identified, or discovered the presence or occurrence of another entity or event.
-
E.
hasModeOfDetection
Indicates that one entity is identified, measured, or observed using a specified method or technique of detection.
- 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_69e2fac889c081908e9ff686cb428e5a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 5:28 a.m.