Triple
T3068017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megan Leavey |
E62152
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Tim Lovestedt
Tim Lovestedt is a screenwriter known for his work on the military drama film "Megan Leavey."
|
E354226
|
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: Tim Lovestedt | Statement: [Megan Leavey, screenwriter, Tim Lovestedt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tim Lovestedt Context triple: [Megan Leavey, screenwriter, Tim Lovestedt]
-
A.
Christian M. Ravndal
Christian M. Ravndal was an American diplomat who served as the United States Ambassador to Hungary.
-
B.
Ralph Høibakk
Ralph Høibakk is a Norwegian mountaineer and engineer known for his pioneering high-altitude climbs, including the first ascent of the Himalayan peak Tirich Mir.
-
C.
Erik Selvig
Erik Selvig is a fictional astrophysicist in the Marvel Cinematic Universe who becomes a close ally of Thor and plays a key role in studying and understanding cosmic phenomena.
-
D.
Kurt Johnstad
Kurt Johnstad is an American screenwriter best known for writing the action films "300" and "Atomic Blonde."
-
E.
Christopher Tellefsen
Christopher Tellefsen is an American film editor known for his work on acclaimed movies such as "A Quiet Place," "Moneyball," and "Capote."
- 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: Tim Lovestedt Triple: [Megan Leavey, screenwriter, Tim Lovestedt]
Generated description
Tim Lovestedt is a screenwriter known for his work on the military drama film "Megan Leavey."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tim Lovestedt Target entity description: Tim Lovestedt is a screenwriter known for his work on the military drama film "Megan Leavey."
-
A.
Christian M. Ravndal
Christian M. Ravndal was an American diplomat who served as the United States Ambassador to Hungary.
-
B.
Ralph Høibakk
Ralph Høibakk is a Norwegian mountaineer and engineer known for his pioneering high-altitude climbs, including the first ascent of the Himalayan peak Tirich Mir.
-
C.
Erik Selvig
Erik Selvig is a fictional astrophysicist in the Marvel Cinematic Universe who becomes a close ally of Thor and plays a key role in studying and understanding cosmic phenomena.
-
D.
Kurt Johnstad
Kurt Johnstad is an American screenwriter best known for writing the action films "300" and "Atomic Blonde."
-
E.
Christopher Tellefsen
Christopher Tellefsen is an American film editor known for his work on acclaimed movies such as "A Quiet Place," "Moneyball," and "Capote."
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fea06881909e5251eea26599ac |
completed | March 8, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3340904b4819097ac23cb2b3fe5d5 |
completed | March 12, 2026, 9:45 p.m. |
| NEDg | Description generation | batch_69b338202d208190a2442e62250785ce |
completed | March 12, 2026, 10:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b344f93b8881909e00f4afe6493e1f |
completed | March 12, 2026, 10:58 p.m. |
Created at: March 8, 2026, 3:02 p.m.