Triple
T37472273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halls of Atonement |
E931181
|
entity |
| Predicate | travelHub |
P191056
|
FINISHED |
| Object | Revendreth flight paths |
—
|
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: Revendreth flight paths | Statement: [Halls of Atonement, travelHub, Revendreth flight paths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelHub Context triple: [Halls of Atonement, travelHub, Revendreth flight paths]
-
A.
travelMechanic
Indicates the method or system by which movement or travel between locations is carried out.
-
B.
travelZone
Indicates a relationship where an entity is located in, moves within, or is permitted to move within a specified geographic or regulatory area.
-
C.
travelScope
Indicates the extent or range within which travel is allowed, intended, or applicable for an entity or activity.
-
D.
travelMarket
Indicates a relationship where an entity participates in or is associated with the commercial exchange, promotion, or sale of travel-related services or experiences.
-
E.
travelRouteContext
Indicates the contextual details (such as purpose, conditions, or circumstances) under which a particular travel route is taken or defined.
- 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_69f76ec2af148190897d101070d7f415 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd866dd248190bff61c43bee93f54 |
completed | May 7, 2026, 6:22 p.m. |
Created at: May 3, 2026, 4:17 p.m.