Triple
T15811559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Pier |
E383365
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object |
Michelle Michael
Michelle Michael is a British businesswoman best known for owning and redeveloping the Grand Pier in Weston-super-Mare.
|
E1178512
|
NE FINISHED |
How this triple was built (4 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: Michelle Michael | Statement: [Grand Pier, owner, Michelle Michael]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle Michael Context triple: [Grand Pier, owner, Michelle Michael]
-
A.
Michelle Mitchenor
Michelle Mitchenor is an American actress best known for her role as Detective Sonya Bailey on the television series "Lethal Weapon."
-
B.
Dani Powell
Dani Powell is a central character in the TV crime drama "Prodigal Son," known for her role as a skilled and determined detective on the NYPD team.
-
C.
Melinda Washington
Melinda Washington is the child of Joshua Washington, known primarily in relation to him.
-
D.
Michelle Stevens
Michelle Stevens is a relatively common personal name that may refer to multiple individuals across different fields, rather than a single widely recognized public figure.
-
E.
Kimberly Wallace
Kimberly Wallace is the sweet, wealthy, and unsuspecting young bride-to-be in the romantic comedy film "My Best Friend's Wedding."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Michelle Michael Triple: [Grand Pier, owner, Michelle Michael]
Generated description
Michelle Michael is a British businesswoman best known for owning and redeveloping the Grand Pier in Weston-super-Mare.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michelle Michael Target entity description: Michelle Michael is a British businesswoman best known for owning and redeveloping the Grand Pier in Weston-super-Mare.
-
A.
Michelle Mitchenor
Michelle Mitchenor is an American actress best known for her role as Detective Sonya Bailey on the television series "Lethal Weapon."
-
B.
Dani Powell
Dani Powell is a central character in the TV crime drama "Prodigal Son," known for her role as a skilled and determined detective on the NYPD team.
-
C.
Melinda Washington
Melinda Washington is the child of Joshua Washington, known primarily in relation to him.
-
D.
Michelle Stevens
Michelle Stevens is a relatively common personal name that may refer to multiple individuals across different fields, rather than a single widely recognized public figure.
-
E.
Kimberly Wallace
Kimberly Wallace is the sweet, wealthy, and unsuspecting young bride-to-be in the romantic comedy film "My Best Friend's Wedding."
- F. None of above. chosen
Provenance (5 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b52bbb888190b226567e84ced7e9 |
completed | April 16, 2026, 10:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff999210148190baa6dcb19be3a1d3 |
completed | May 9, 2026, 8:31 p.m. |
| NEDg | Description generation | batch_69ff9aa845348190907116612d2c87cd |
completed | May 9, 2026, 8:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff9b8833b88190967db29027b5f987 |
completed | May 9, 2026, 8:39 p.m. |
Created at: April 10, 2026, 4:49 a.m.