Triple
T3579693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alva Erskine Vanderbilt |
E75769
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Alva |
E21163
|
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: Alva | Statement: [Alva Erskine Vanderbilt, givenName, Alva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alva Context triple: [Alva Erskine Vanderbilt, givenName, Alva]
-
A.
Alva
chosen
Alva is the middle name of the famed American inventor Thomas Edison, often used as part of his full name, Thomas Alva Edison.
-
B.
Alva
Alva is a small town in central Scotland situated at the foot of the Ochil Hills in Clackmannanshire.
-
C.
Alva
Alva is a small city in northwestern Oklahoma known as the county seat of Woods County and home to Northwestern Oklahoma State University.
-
D.
Neilia
Neilia was an American educator best known as the first wife of Joe Biden, who tragically died in a car accident in 1972 along with their infant daughter.
-
E.
Henrike
Henrike is a feminine given name of German origin, serving as the female form of Heinrich.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0ffecdc8190bf01c8ba90e3733e |
completed | March 8, 2026, 6:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3bbc6bc948190a517639f5d79c0a3 |
completed | March 13, 2026, 7:24 a.m. |
Created at: March 8, 2026, 3:21 p.m.