Triple
T23269437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DAMA/LIBRA |
E588247
|
entity |
| Predicate | aimsToDetect |
P151609
|
FINISHED |
| Object | dark matter |
—
|
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: dark matter | Statement: [DAMA/LIBRA, aimsToDetect, dark matter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimsToDetect Context triple: [DAMA/LIBRA, aimsToDetect, dark matter]
-
A.
aimsToDistinguish
Indicates an intention or effort by one entity to set itself or something else apart from others by highlighting differences or unique characteristics.
-
B.
aimsToCapture
Indicates an intention or effort by one entity to take control of, seize, or gain possession of another entity.
-
C.
aimOf
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
-
D.
detected
Indicates that an entity has observed, identified, or discovered the presence or occurrence of another entity or event.
-
E.
aimsToMeasure
Indicates that one entity is intended or designed to quantify, assess, or evaluate another entity or property.
- F. None of above. chosen
Provenance (4 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_69e25d148adc819088efbf42672604e9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1957219188190b30bceffad1542da |
completed | April 29, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:45 p.m.