Triple
T6244304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long John Silver |
E139678
|
entity |
| Predicate | hasBodyPartProsthetic |
P54723
|
FINISHED |
| Object | wooden leg (implied) |
—
|
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: wooden leg (implied) | Statement: [Long John Silver, hasBodyPartProsthetic, wooden leg (implied)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyPartProsthetic Context triple: [Long John Silver, hasBodyPartProsthetic, wooden leg (implied)]
-
A.
hasProsthesis
chosen
Indicates that an entity possesses or is equipped with an artificial substitute for a missing or impaired body part.
-
B.
hasLimb
Indicates that an entity possesses a specific limb as part of its body.
-
C.
hasExoskeleton
Indicates that an entity possesses an external supportive or protective skeletal structure covering its body.
-
D.
hasCybernetic
Indicates that an entity possesses or is equipped with cybernetic enhancements, implants, or components.
-
E.
lostLimb
Indicates that an entity has had one or more of its limbs removed or rendered permanently absent, typically as a result of injury, surgery, or trauma.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0631c63d48190a41ec1232aecb373 |
completed | March 22, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c056037bf88190a0a3fe7429345d0b |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:23 p.m.