Triple
T6991900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J. Thaddeus Toad |
E162103
|
entity |
| Predicate | vehicleObsession |
P74328
|
FINISHED |
| Object | motorcar |
—
|
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: motorcar | Statement: [J. Thaddeus Toad, vehicleObsession, motorcar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleObsession Context triple: [J. Thaddeus Toad, vehicleObsession, motorcar]
-
A.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
B.
drives
Indicates that one entity operates and controls the movement of a vehicle or similar conveyance transporting themselves or others.
-
C.
musicVehicle
Indicates a relationship where a vehicle is associated with or used for playing, broadcasting, or producing music.
-
D.
notableCar
Indicates that the subject is a car recognized for its significance, prominence, or special interest (e.g., historically, culturally, or technically).
-
E.
mainVehicle
Indicates that one vehicle is the primary or most important vehicle associated with a given entity or context.
- F. None of above. chosen
Provenance (4 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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbc1f63c8190837cfd71cf5ed613 |
completed | March 27, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c4a18881908d267137daed828b |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6dbbc00fc8190a18221524b774021 |
completed | March 27, 2026, 7:34 p.m. |
Created at: March 27, 2026, 2:32 p.m.