Triple
T3364412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henrietta Hill Swope |
E70800
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Henrietta |
E77681
|
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: Henrietta | Statement: [Henrietta Hill Swope, givenName, Henrietta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henrietta Context triple: [Henrietta Hill Swope, givenName, Henrietta]
-
A.
Henrietta
chosen
Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
-
B.
Henriette
Henriette is the given first name of the French photographer and painter Dora Maar, renowned for her association with Pablo Picasso and the Surrealist movement.
-
C.
Mariette
Mariette is a French feminine given name, commonly used as a diminutive or affectionate form of Marie.
-
D.
Pauletta
Pauletta is a feminine given name, typically considered a diminutive or variant of Paula or Pauline.
-
E.
Oona
Oona O’Neill was an American socialite and actress best known as the fourth wife of legendary filmmaker Charlie Chaplin and the daughter of playwright Eugene O’Neill.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb28467b88190bdf70b851bc8efa9 |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b334332ce88190b898894286c166c2 |
completed | March 12, 2026, 9:46 p.m. |
Created at: March 8, 2026, 3:13 p.m.