Triple
T4446784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alma Reville |
E96307
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Alma |
E53488
|
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: Alma | Statement: [Alma Reville, givenName, Alma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alma Context triple: [Alma Reville, givenName, Alma]
-
A.
Alma
chosen
Alma is a historic wooden scow schooner preserved as a museum ship in San Francisco, representing the city’s 19th- and early 20th-century maritime commerce.
-
B.
Alma
Alma is a historic British Army battle honour commemorating the Battle of the Alma in the Crimean War.
-
C.
Ellah
Ellah is a given name, typically used as a feminine variant of the name Ella.
-
D.
Nena
Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
-
E.
Zella
Zella is an activewear and athleisure clothing brand known for its performance-focused yet stylish designs, sold at Nordstrom.
- 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355d31e10819086590b9f828d50b0 |
completed | March 13, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b61386df48819080e44a23b9d67d23 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:32 p.m.