Triple

T14732234
Position Surface form Disambiguated ID Type / Status
Subject Keith Neudecker E346103 entity
Predicate spouse P13 FINISHED
Object Lianne
Lianne is a fictional character in Don DeLillo's novel "Falling Man," known as the estranged wife of protagonist Keith Neudecker and a woman struggling to cope with the aftermath of the September 11 attacks.
 E345172 NE FINISHED

How this triple was built (4 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, spouse, Lianne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lianne
Context triple: [Keith Neudecker, spouse, Lianne]
  • A. Lianne
    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 a river in Albania that flows through the capital city of Tirana before joining the Tirana River.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lianne
Triple: [Keith Neudecker, spouse, Lianne]
Generated description
Lianne is a fictional character in Don DeLillo's novel "Falling Man," known as the estranged wife of protagonist Keith Neudecker and a woman struggling to cope with the aftermath of the September 11 attacks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lianne
Target entity description: Lianne is a fictional character in Don DeLillo's novel "Falling Man," known as the estranged wife of protagonist Keith Neudecker and a woman struggling to cope with the aftermath of the September 11 attacks.
  • 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 the ISO 15924 four-letter code used to represent the Tai Tham script in international standards.
  • E. Lana
    Lana is a filmmaker best known as one of the Wachowski sisters, the co-creators of The Matrix film series.
  • F. None of above.

Provenance (5 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_69fdfb89ea388190b356df74e36023f7 completed May 8, 2026, 3:04 p.m.
NEDg Description generation batch_69fdfdd73dcc8190bd0340b2f2a2c54a completed May 8, 2026, 3:14 p.m.
NED2 Entity disambiguation (via description) batch_69fdfe70e03481909eb9a9bf863f826b completed May 8, 2026, 3:17 p.m.
Created at: April 10, 2026, 1:29 a.m.