Triple
T37605825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Louis Stevenson Trail (GR 70) |
E935648
|
entity |
| Predicate | followsJourneyDescribedIn |
P2127
|
FINISHED |
| Object | Travels with a Donkey in the Cévennes |
—
|
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: Travels with a Donkey in the Cévennes | Statement: [Robert Louis Stevenson Trail (GR 70), followsJourneyDescribedIn, Travels with a Donkey in the Cévennes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsJourneyDescribedIn Context triple: [Robert Louis Stevenson Trail (GR 70), followsJourneyDescribedIn, Travels with a Donkey in the Cévennes]
-
A.
followsTour
Indicates that one entity attends or participates in a tour that occurs after, or as a consequence of, another specified event or tour.
-
B.
followsIn
Indicates that one entity comes after or succeeds another in a sequence, order, or progression.
-
C.
followsBy
Indicates that one event, state, or entity occurs or comes immediately after another in a sequence or order.
-
D.
followsRouteOf
chosen
Indicates that one entity travels along the same path or route that another entity takes or has taken.
-
E.
followsBetween
Indicates that one entity comes after or succeeds another entity within a specified context or sequence.
- 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_69f76ed0a85481909254a8a89090c826 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff7ae5d088819089aa3b6360b6b749 |
completed | May 9, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69ff7a4df6488190bf60d675b36b1d6d |
completed | May 9, 2026, 6:17 p.m. |
Created at: May 3, 2026, 4:18 p.m.