Triple
T4942568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stacy Lattisaw |
E110972
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lattisaw |
E464572
|
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: Lattisaw | Statement: [Stacy Lattisaw, familyName, Lattisaw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lattisaw Context triple: [Stacy Lattisaw, familyName, Lattisaw]
-
A.
Kashmore
Kashmore is a town in Pakistan’s Sindh province that serves as a regional hub near the Guddu Barrage on the Indus River.
-
B.
Tilghman
Tilghman is a masculine given name of English origin that has been borne by various notable American figures, including politicians and military officers.
-
C.
Rilland
Rilland is a village in the Dutch province of Zeeland, located on the island of Zuid-Beveland.
-
D.
Considine
chosen
Considine is a surname of Irish origin borne by various notable individuals in fields such as politics, entertainment, and sports.
-
E.
Warley
Warley is a locality within the Brentwood Borough of Essex, England, known primarily as a residential suburb with historical military and institutional connections.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70a5f56481908365d0fe16892bf4 |
completed | March 20, 2026, 4:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77c421288190bcc2d9bfdfff7198 |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:31 p.m.