Triple
T18175931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ravenscraig former steelworks site |
E435159
|
entity |
| Predicate | economicRolePast |
P130749
|
FINISHED |
| Object | large industrial employer in North Lanarkshire |
—
|
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: large industrial employer in North Lanarkshire | Statement: [Ravenscraig former steelworks site, economicRolePast, large industrial employer in North Lanarkshire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicRolePast Context triple: [Ravenscraig former steelworks site, economicRolePast, large industrial employer in North Lanarkshire]
-
A.
namedAfterOccupationOrRole
Indicates that an entity is named after a specific occupation, profession, or social role associated with a person or group.
-
B.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
C.
roleDuringOccupation
Indicates the specific role or position an entity held during a particular occupation or period of control.
-
D.
hasPastOccupation
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
E.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df59bf3881909adc28cacbe9cb39 |
completed | April 19, 2026, 1:57 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:30 a.m.