Triple
T14744942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joel Goodson |
E346442
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Lana |
E346443
|
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: Lana | Statement: [Joel Goodson, associatedWith, Lana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lana Context triple: [Joel Goodson, associatedWith, Lana]
-
A.
Lana
Lana is a filmmaker best known as one of the Wachowski sisters, the co-creators of The Matrix film series.
-
B.
Lana
Lana is a river in Albania that flows through the capital city of Tirana before joining the Tirana River.
-
C.
Lana
Lana is the ISO 15924 four-letter code used to represent the Tai Tham script in international standards.
-
D.
Lana
Lana is a professional wrestler and television personality best known for her time in WWE, where she appeared prominently as a manager and in-ring performer.
-
E.
Lana
chosen
Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d002708190a32a4a45e96fc389 |
completed | April 14, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe38894a2481908dd219ecaa7f3a3c |
completed | May 8, 2026, 7:24 p.m. |
Created at: April 10, 2026, 1:30 a.m.