Triple
T14523300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Jane |
E340705
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Ayesha Hauer
Ayesha Hauer is a Swiss-born actress known for her roles in films such as "Kick of Death" and as the daughter of acclaimed actor Rutger Hauer.
|
E1104533
|
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: Ayesha Hauer | Statement: [Thomas Jane, spouse, Ayesha Hauer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayesha Hauer Context triple: [Thomas Jane, spouse, Ayesha Hauer]
-
A.
Anisa George
Anisa George is an actress known for her role in the critically acclaimed drama film "Rachel Getting Married."
-
B.
Najia Khan
Najia Khan is a member of the Khan family and a relative of Yasmin Khan.
-
C.
Ritika Sajdeh
Ritika Sajdeh is an Indian sports manager and public figure best known for her association with prominent cricketers and her marriage to Indian cricket star Rohit Sharma.
-
D.
Nikita Gill
Nikita Gill is a contemporary British-Indian poet and writer known for her emotionally resonant, feminist poetry and modern retellings of myths and fairy tales.
-
E.
Sheena Etranzi
Sheena Etranzi is a playable commando character in the run-and-gun video game Contra: Hard Corps, known for her agility and combat prowess.
- 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: Ayesha Hauer Triple: [Thomas Jane, spouse, Ayesha Hauer]
Generated description
Ayesha Hauer is a Swiss-born actress known for her roles in films such as "Kick of Death" and as the daughter of acclaimed actor Rutger Hauer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ayesha Hauer Target entity description: Ayesha Hauer is a Swiss-born actress known for her roles in films such as "Kick of Death" and as the daughter of acclaimed actor Rutger Hauer.
-
A.
Anisa George
Anisa George is an actress known for her role in the critically acclaimed drama film "Rachel Getting Married."
-
B.
Najia Khan
Najia Khan is a member of the Khan family and a relative of Yasmin Khan.
-
C.
Ritika Sajdeh
Ritika Sajdeh is an Indian sports manager and public figure best known for her association with prominent cricketers and her marriage to Indian cricket star Rohit Sharma.
-
D.
Nikita Gill
Nikita Gill is a contemporary British-Indian poet and writer known for her emotionally resonant, feminist poetry and modern retellings of myths and fairy tales.
-
E.
Sheena Etranzi
Sheena Etranzi is a playable commando character in the run-and-gun video game Contra: Hard Corps, known for her agility and combat prowess.
- F. None of above. chosen
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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea04f16f88190ba357b0f8021b46b |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a50324481909713bbf68295e839 |
completed | May 8, 2026, 5:53 a.m. |
| NEDg | Description generation | batch_69fd7c52e0bc8190b8c4b270653e65df |
completed | May 8, 2026, 6:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd7cf3088c8190a3bf53c9599f0304 |
completed | May 8, 2026, 6:04 a.m. |
Created at: April 10, 2026, 1:22 a.m.