Triple
T144214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert |
E2918
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Bob |
E31255
|
NE 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: Bob | Statement: [Robert, hasVariant, Bob]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bob Context triple: [Robert, hasVariant, Bob]
-
A.
Jack
Jack is a common masculine given name, often used as a familiar form of John and widely featured in English-language literature and popular culture.
-
B.
Rob
chosen
Rob is a common shortened form of the given name Robert, frequently used as an informal or familiar first name.
-
C.
Barry
Barry is a coastal town and popular seaside resort in the Vale of Glamorgan, South Wales, known for Barry Island and its beaches.
-
D.
Bill
Bill is a common masculine given name, typically used as a diminutive or nickname for William.
-
E.
Bert
Bert is the given name of Bert Hölldobler, a renowned German behavioral biologist and sociobiologist known for his pioneering research on ants and social insects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257e935bc8190a03e54a10e9ba6f7 |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3736b2ff081909a5b36a93fa16130 |
completed | Feb. 28, 2026, 10:59 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.