Triple
T30732445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adventure of the Three Gables |
E782458
|
entity |
| Predicate | hasDetectivePartner |
P63938
|
FINISHED |
| Object | Dr. John Watson |
—
|
NE NERFINISHED |
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: Dr. John Watson | Statement: [The Adventure of the Three Gables, hasDetectivePartner, Dr. John Watson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDetectivePartner Context triple: [The Adventure of the Three Gables, hasDetectivePartner, Dr. John Watson]
-
A.
hasPolicePartner
Indicates that one entity has another entity as its partner in a police or law-enforcement context.
-
B.
hasClericalDetective
Indicates that an entity includes or is associated with a detective who is also a member of the clergy.
-
C.
hasFictionalDetective
chosen
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
D.
hasPartner
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
-
E.
partnerInCrime
Indicates a relationship where two or more entities collaborate closely in committing or planning wrongful, illicit, or mischievous acts together.
- 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_69f224ad9f9c81908e02a79ae0001137 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fde49a084081909d99b1e0258169d5 |
completed | May 8, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69fde1d04bd881909a46ecbbf18dfe59 |
completed | May 8, 2026, 1:14 p.m. |
Created at: April 29, 2026, 8:37 p.m.