Triple
T31293883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smoothfield Holding Limited |
E798021
|
entity |
| Predicate | relationshipToMitchellsAndButlers |
P207399
|
FINISHED |
| Object | long‑term strategic investor |
—
|
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: long‑term strategic investor | Statement: [Smoothfield Holding Limited, relationshipToMitchellsAndButlers, long‑term strategic investor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMitchellsAndButlers Context triple: [Smoothfield Holding Limited, relationshipToMitchellsAndButlers, long‑term strategic investor]
-
A.
relationToAndrewMartin
Indicates a relationship that specifies how one entity is connected or related to Andrew Martin.
-
B.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
-
C.
relationshipToCatherine
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
-
D.
relationshipWithSybilFawlty
Indicates the type or nature of a relationship that an entity has with Sybil Fawlty.
-
E.
familyRelationToCharltons
Indicates the type of familial relationship an entity has to the Charltons.
- 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_69f224dfde288190af313f3c221c857e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 9:14 p.m.