Triple
T8653024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porsche 944 |
E205144
|
entity |
| Predicate | designer |
P184
|
FINISHED |
| Object |
Harm Lagaay
Harm Lagaay is a Dutch automobile designer best known for his influential work at Porsche, where he helped shape several iconic sports car models.
|
E748610
|
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: Harm Lagaay | Statement: [Porsche 944, designer, Harm Lagaay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harm Lagaay Context triple: [Porsche 944, designer, Harm Lagaay]
-
A.
Biktima
Biktima is a Filipino thriller-drama film starring Cesar Montano that centers on crime, trauma, and the pursuit of justice.
-
B.
Maltrata
Maltrata is a municipality in the Mexican state of Veracruz, located in the mountainous central region and integrated into the Orizaba metropolitan area.
-
C.
Ikalahan
Ikalahan is an indigenous people of the northern Philippines whose name is also used for their native Kalanguya language.
-
D.
Malice
Malice is an American rapper and member of the hip hop duo Clipse, known for his intricate wordplay and reflective lyricism.
-
E.
Malice
Malice is a 1993 psychological thriller film, co-written by Aaron Sorkin, known for its twist-filled plot involving murder, deception, and a brilliant but sinister surgeon.
- 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: Harm Lagaay Triple: [Porsche 944, designer, Harm Lagaay]
Generated description
Harm Lagaay is a Dutch automobile designer best known for his influential work at Porsche, where he helped shape several iconic sports car models.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harm Lagaay Target entity description: Harm Lagaay is a Dutch automobile designer best known for his influential work at Porsche, where he helped shape several iconic sports car models.
-
A.
Biktima
Biktima is a Filipino thriller-drama film starring Cesar Montano that centers on crime, trauma, and the pursuit of justice.
-
B.
Maltrata
Maltrata is a municipality in the Mexican state of Veracruz, located in the mountainous central region and integrated into the Orizaba metropolitan area.
-
C.
Ikalahan
Ikalahan is an indigenous people of the northern Philippines whose name is also used for their native Kalanguya language.
-
D.
Malice
Malice is an American rapper and member of the hip hop duo Clipse, known for his intricate wordplay and reflective lyricism.
-
E.
Malice
Malice is a 1993 psychological thriller film, co-written by Aaron Sorkin, known for its twist-filled plot involving murder, deception, and a brilliant but sinister surgeon.
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc484206d881908017897dada63124 |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccd1d7f88190a5440581325eac63 |
completed | April 2, 2026, 8:08 p.m. |
| NEDg | Description generation | batch_69cece8c4bdc8190988990c675f50f86 |
completed | April 2, 2026, 8:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cecf3a0e78819082cc7c43eceae309 |
completed | April 2, 2026, 8:19 p.m. |
Created at: March 30, 2026, 6:29 p.m.