Triple
T6860250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Townsend Harris |
E158258
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Townsend |
E270517
|
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: Townsend | Statement: [Townsend Harris, givenName, Townsend]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Townsend Context triple: [Townsend Harris, givenName, Townsend]
-
A.
Townsend
chosen
Townsend is a surname of English origin borne by numerous notable individuals across fields such as politics, science, and the arts.
-
B.
Tilton
Tilton is a locality in the United Kingdom notable for lending its name to the territorial designation of the peerage title Baron Keynes of Tilton.
-
C.
Faison
Faison is a surname most notably associated with American actor and comedian Donald Faison.
-
D.
Winslow
Winslow is the main commercial and residential hub of Bainbridge Island, Washington, known for its downtown shops, restaurants, and ferry terminal connecting to Seattle.
-
E.
Winslow
Winslow is a small historic market town in Buckinghamshire, England, known for its traditional architecture and rural surroundings.
- 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_69c68830cdbc8190a8301c7a9d9f651a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8737fac81909fc546ca2bf6a278 |
completed | March 27, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72fe79af081909baacbfd4d5e8f24 |
completed | March 28, 2026, 1:33 a.m. |
Created at: March 27, 2026, 2:21 p.m.