Triple
T7326094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grays |
E168878
|
entity |
| Predicate | postTown |
P2711
|
FINISHED |
| Object |
GRAYS
GRAYS is a town in Essex, England, situated on the north bank of the River Thames and serving as a local commercial and residential center.
|
E656559
|
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: GRAYS | Statement: [Grays, postTown, GRAYS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GRAYS Context triple: [Grays, postTown, GRAYS]
-
A.
Gray
Gray is the commonly used short form of the name Gray Davis, the former governor of California.
-
B.
Gray
Gray is a historic commune in eastern France known for its picturesque setting along the Saône River and its well-preserved old town.
-
C.
Gray
Gray is a common English surname of Anglo-Saxon origin, often associated with families from Britain and Ireland.
-
D.
Grey
Grey is a common English surname borne by numerous notable figures across entertainment, politics, and history.
-
E.
Isabel Jeans
Isabel Jeans was a British stage and film actress known for her sophisticated roles in early 20th-century cinema, including appearances in several Alfred Hitchcock films.
- 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: GRAYS Triple: [Grays, postTown, GRAYS]
Generated description
GRAYS is a town in Essex, England, situated on the north bank of the River Thames and serving as a local commercial and residential center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GRAYS Target entity description: GRAYS is a town in Essex, England, situated on the north bank of the River Thames and serving as a local commercial and residential center.
-
A.
Gray
Gray is the commonly used short form of the name Gray Davis, the former governor of California.
-
B.
Gray
Gray is a historic commune in eastern France known for its picturesque setting along the Saône River and its well-preserved old town.
-
C.
Gray
Gray is a common English surname of Anglo-Saxon origin, often associated with families from Britain and Ireland.
-
D.
Grey
Grey is a common English surname borne by numerous notable figures across entertainment, politics, and history.
-
E.
Isabel Jeans
Isabel Jeans was a British stage and film actress known for her sophisticated roles in early 20th-century cinema, including appearances in several Alfred Hitchcock films.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a612c08190b7a3fefa811bbcec |
completed | March 27, 2026, 9:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ef0e3e7481908e6cedbd3f0077ca |
completed | March 28, 2026, 3:09 p.m. |
| NEDg | Description generation | batch_69c7efa4f5148190842f30988cbea94c |
completed | March 28, 2026, 3:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7f0092bac819080ded1863f99290a |
completed | March 28, 2026, 3:13 p.m. |
Created at: March 27, 2026, 3:03 p.m.