Triple
T14732240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keith Neudecker |
E346103
|
entity |
| Predicate | relationshipWith |
P10260
|
FINISHED |
| Object | Lianne |
E345172
|
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: Lianne | Statement: [Keith Neudecker, relationshipWith, Lianne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lianne Context triple: [Keith Neudecker, relationshipWith, Lianne]
-
A.
Lianne
chosen
Lianne is a central character in Don DeLillo’s novel "Falling Man," depicted as a woman grappling with personal and familial upheaval in the aftermath of the September 11 attacks.
-
B.
Lorna
Lorna is a feminine given name most notably borne by American actress and singer Lorna Luft, the daughter of Judy Garland.
-
C.
Lana
Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
-
D.
Lana
Lana is a filmmaker best known as one of the Wachowski sisters, the co-creators of The Matrix film series.
-
E.
Lana
Lana is the ISO 15924 four-letter code used to represent the Tai Tham script in international standards.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec26311c8819093a81ff0fa43b33b |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0ce3d1d88190951e88bef88db500 |
completed | May 8, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:29 a.m.