Triple
T13493754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blisworth Tunnel |
E320705
|
entity |
| Predicate | originallyLeggedThrough |
P110625
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Blisworth Tunnel, originallyLeggedThrough, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originallyLeggedThrough Context triple: [Blisworth Tunnel, originallyLeggedThrough, true]
-
A.
originallyHad
Indicates that an entity previously possessed, contained, or was associated with something before a change, loss, or transformation occurred.
-
B.
secondLegOrigin
Indicates the location from which the second leg of a multi-leg journey or route begins.
-
C.
ownedThrough
Indicates that one entity possesses or controls another indirectly via an intermediate entity, structure, or arrangement (such as a subsidiary, trust, or other vehicle).
-
D.
firstLeg
Indicates that one entity represents the initial segment or starting portion of a multi-part journey, sequence, or process involving another entity.
-
E.
hasFootCrossing
Indicates that one entity has a designated crossing point specifically intended for pedestrians on foot.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf4da2c88190a867b53529d39545 |
completed | April 12, 2026, 2:42 p.m. |
| PD | Predicate disambiguation | batch_69dbae06061881909a6a6032e0507587 |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:43 p.m.