Triple
T16191133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timothy Dowling |
E392941
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Timothy |
unclear NED1
|
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: Timothy | Statement: [Timothy Dowling, givenName, Timothy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timothy Context triple: [Timothy Dowling, givenName, Timothy]
-
A.
Timothy
Timothy is the given first name of Sir Tim Berners-Lee, the British computer scientist who invented the World Wide Web.
-
B.
Timothy
Timothy is the given name of British actor Tim Pigott-Smith, known for his work in film, television, and theatre.
-
C.
Timothy
Timothy is a minor character in Enid Blyton’s adventure novel "Five on a Treasure Island," appearing alongside the Famous Five in their first mystery.
-
D.
Timothy
Timothy is the given first name of American film director and producer Tim Story, known for movies like "Barbershop" and the "Fantastic Four" films.
-
E.
Timothy
Timothy is a prominent early Christian companion and protégé of the Apostle Paul, known from the New Testament for his missionary work and pastoral leadership.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d5769c8190bbb604bfa095a1a5 |
completed | April 17, 2026, 12:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff095504819096c36d6c5d131207 |
completed | May 10, 2026, 3:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.