Triple
T37837108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Beebe |
E943366
|
entity |
| Predicate | hallmarkTrait |
P167560
|
FINISHED |
| Object | never-give-up attitude |
—
|
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: never-give-up attitude | Statement: [Don Beebe, hallmarkTrait, never-give-up attitude]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hallmarkTrait Context triple: [Don Beebe, hallmarkTrait, never-give-up attitude]
-
A.
distinguishingTrait
Indicates that a particular characteristic or feature uniquely differentiates one entity from another.
-
B.
iconicTrait
chosen
Indicates that a trait is emblematic or strongly characteristic of an entity, making it widely recognized as a defining feature of that entity.
-
C.
loreTrait
Indicates that an entity possesses a specific lore-related characteristic or attribute within a fictional or narrative context.
-
D.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
E.
spanCharacteristic
Indicates that one entity has a particular measurable or descriptive property that characterizes the extent, duration, or range of another entity or phenomenon.
- 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.