Triple
T3385422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carla Gugino |
E71289
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Carla |
E101410
|
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: Carla | Statement: [Carla Gugino, givenName, Carla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carla Context triple: [Carla Gugino, givenName, Carla]
-
A.
Carla
chosen
Carla is a feminine given name commonly used in various languages, often considered the female form of Carl or Charles.
-
B.
Carole
Carole is a feminine given name of French origin, commonly used in English-speaking countries.
-
C.
Carine
Carine is a feminine given name, often considered a variant of names like Catherine or Karine, used in various European languages.
-
D.
Karin
Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
-
E.
Carlie
Carlie is a feminine given name, often used as a variant of Carly or Carley.
- 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_69ad85a8fd9c819095ecedf838d2bf1b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb5ee5e188190912dcea494a12038 |
completed | March 8, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b33455ae2481908e6478cb240b31c1 |
completed | March 12, 2026, 9:47 p.m. |
Created at: March 8, 2026, 3:14 p.m.