Triple
T23634067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sapphire |
E583692
|
entity |
| Predicate | hasTenacity |
P67874
|
FINISHED |
| Object | tough |
—
|
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: tough | Statement: [Sapphire, hasTenacity, tough]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTenacity Context triple: [Sapphire, hasTenacity, tough]
-
A.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
B.
isResistant
chosen
Indicates that an entity can withstand, oppose, or is not significantly affected by a specified force, influence, or agent.
-
C.
hasTopness
Indicates that an entity possesses the quantum property of topness, typically associated with the presence or contribution of a top quark.
-
D.
hasTendency
Indicates that an entity is inclined or likely to exhibit a particular behavior, characteristic, or outcome under certain conditions.
-
E.
hasPassion
Indicates that one entity feels a strong enthusiasm, interest, or love for another entity, activity, or subject.
- 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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b1eb38a481909f7ceeaefb7b43ce |
completed | April 29, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:47 p.m.