Triple
T8530427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lea Thompson |
E201931
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lea |
E223643
|
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: Lea | Statement: [Lea Thompson, givenName, Lea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lea Context triple: [Lea Thompson, givenName, Lea]
-
A.
Lea
chosen
Lea is a given name used across various cultures, often as a variant of Leah or Léa.
-
B.
Letta
Letta is an Italian surname most prominently associated with political figures such as Gianni Letta and former Prime Minister Enrico Letta.
-
C.
Lela
Lela is a feminine given name used in various cultures, often as a variant of Leila or Layla.
-
D.
Laleia
Laleia is a town in northern Timor-Leste known as the birthplace of independence leader and former president Xanana Gusmão.
-
E.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe67546248190b359c845c0161ad3 |
completed | March 31, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6d68d14c81908bde8ca0113f9503 |
completed | April 2, 2026, 1:21 p.m. |
Created at: March 30, 2026, 6:17 p.m.