Triple
T17242967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indochinese tiger |
E418547
|
entity |
| Predicate | stripeCharacteristics |
P101268
|
FINISHED |
| Object | darker stripes |
—
|
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: darker stripes | Statement: [Indochinese tiger, stripeCharacteristics, darker stripes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stripeCharacteristics Context triple: [Indochinese tiger, stripeCharacteristics, darker stripes]
-
A.
ruleCharacteristics
Indicates the defining properties, constraints, or parameters that specify how a particular rule operates or should be applied.
-
B.
spanCharacteristic
Indicates that one entity has a particular measurable or descriptive property that characterizes the extent, duration, or range of another entity or phenomenon.
-
C.
termCharacteristics
Indicates the defining properties, attributes, or features that characterize a given term.
-
D.
identityFeatures
chosen
Indicates that certain characteristics or attributes are used to define, distinguish, or uniquely identify an entity.
-
E.
valueCharacteristic
Indicates that one entity serves as a value or specific quantitative/qualitative measure that characterizes or describes another entity.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e21003c81908c884a3c8712676a |
completed | April 19, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_69e3832553ac819091aa917c84f755b6 |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.