Triple
T13384350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good Girls |
E319400
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Mila Jojovich
Mila Jojovich is likely an actress known for appearing in the television series "Good Girls."
|
E1036398
|
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: Mila Jojovich | Statement: [Good Girls, castMember, Mila Jojovich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mila Jojovich Context triple: [Good Girls, castMember, Mila Jojovich]
-
A.
Stana Katic
Stana Katic is a Canadian-American actress best known for her role as Detective Kate Beckett on the television series "Castle."
-
B.
Tatiana Pajkovic
Tatiana Pajkovic is a Danish actress and musician known for her work in film and television and for her marriage to actor Boyd Holbrook.
-
C.
Marina Preko
Marina Preko is a small coastal marina and harbor facility located in the town of Preko on the island of Ugljan, Croatia, serving boaters and yachts in the Zadar area.
-
D.
Neyla Pekarek
Neyla Pekarek is an American cellist and singer best known for her work with the folk-rock band The Lumineers.
-
E.
Kara Milovy
Kara Milovy is a Czechoslovak cellist and Bond girl who becomes James Bond’s ally and love interest in the 1987 film "The Living Daylights."
- 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: Mila Jojovich Triple: [Good Girls, castMember, Mila Jojovich]
Generated description
Mila Jojovich is likely an actress known for appearing in the television series "Good Girls."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mila Jojovich Target entity description: Mila Jojovich is likely an actress known for appearing in the television series "Good Girls."
-
A.
Stana Katic
Stana Katic is a Canadian-American actress best known for her role as Detective Kate Beckett on the television series "Castle."
-
B.
Tatiana Pajkovic
Tatiana Pajkovic is a Danish actress and musician known for her work in film and television and for her marriage to actor Boyd Holbrook.
-
C.
Marina Preko
Marina Preko is a small coastal marina and harbor facility located in the town of Preko on the island of Ugljan, Croatia, serving boaters and yachts in the Zadar area.
-
D.
Neyla Pekarek
Neyla Pekarek is an American cellist and singer best known for her work with the folk-rock band The Lumineers.
-
E.
Kara Milovy
Kara Milovy is a Czechoslovak cellist and Bond girl who becomes James Bond’s ally and love interest in the 1987 film "The Living Daylights."
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce80158819082156eaeaeda3bd8 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7268cf04c8190a35fd48ce81c149e |
completed | May 3, 2026, 10:42 a.m. |
| NEDg | Description generation | batch_69f7276776ec81908769cd9f1cc4707e |
completed | May 3, 2026, 10:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7280cbb6c819090bee7862e00b900 |
completed | May 3, 2026, 10:48 a.m. |
Created at: April 9, 2026, 9:33 p.m.