Triple
T3907619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian |
E87241
|
entity |
| Predicate | variantForm |
P4680
|
FINISHED |
| Object | Brien |
E186599
|
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: Brien | Statement: [Brian, variantForm, Brien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brien Context triple: [Brian, variantForm, Brien]
-
A.
Brenner
Brenner is a surname of German origin borne by various notable individuals across fields such as science, politics, and the arts.
-
B.
Rennahan
Rennahan is a surname most notably associated with Ray Rennahan, an American cinematographer known for his pioneering work with Technicolor.
-
C.
Brion
Brion is a surname most notably associated with American musician, composer, and record producer Jon Brion.
-
D.
Bryan
chosen
Bryan is a masculine given name of Celtic origin that is widely used in English-speaking countries.
-
E.
Bryan
Bryan is a mid-sized city in Central Texas known for its close association with neighboring College Station and Texas A&M University.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed13bb14819096842c6c82342524 |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51caf41c881909c5156480b46e794 |
completed | March 14, 2026, 8:30 a.m. |
Created at: March 9, 2026, 3:22 p.m.