Triple
T1108435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Watson |
E25538
|
entity |
| Predicate | observesFromTrain |
P20345
|
FINISHED |
| Object | Tom Watson’s house |
—
|
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: Tom Watson’s house | Statement: [Rachel Watson, observesFromTrain, Tom Watson’s house]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: observesFromTrain Context triple: [Rachel Watson, observesFromTrain, Tom Watson’s house]
-
A.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
observedVia
chosen
Indicates that something is perceived, detected, or measured through a particular medium, instrument, method, or channel.
-
C.
observedBy
Indicates that an entity is perceived, monitored, or recorded by another entity acting as the observer.
-
D.
notableTrain
Indicates that there is a train or rail service associated with the subject that is considered notable or significant in some way.
-
E.
observationType
Indicates the specific kind or category of observation being made or recorded in a given context.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9e6134481909f348986a25f65c6 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b749e2a881909ef28745a7d2d917 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:43 p.m.