Triple
T7656952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Ottman |
E173407
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Ottman
Ottman is a surname most notably associated with John Ottman, an American film editor and composer known for his work on major Hollywood films.
|
E679152
|
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: Ottman | Statement: [John Ottman, familyName, Ottman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ottman Context triple: [John Ottman, familyName, Ottman]
-
A.
Otomian
Otomian is a branch of the Oto-Manguean language family that comprises several closely related indigenous languages spoken in central Mexico.
-
B.
Osmanoğlu
Osmanoğlu is the surname borne by descendants of the Ottoman imperial dynasty, historically associated with the ruling house of the Ottoman Empire.
-
C.
Mahmut
Mahmut is a masculine given name commonly used in Turkish and related cultures, derived from the Arabic name Mahmoud.
-
D.
Gazi
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
-
E.
Gaziosmanpaşa
Gaziosmanpaşa is a densely populated residential and commercial district on the European side of Istanbul, known for its rapid urbanization and diverse working- and middle-class communities.
- 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: Ottman Triple: [John Ottman, familyName, Ottman]
Generated description
Ottman is a surname most notably associated with John Ottman, an American film editor and composer known for his work on major Hollywood films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ottman Target entity description: Ottman is a surname most notably associated with John Ottman, an American film editor and composer known for his work on major Hollywood films.
-
A.
Otomian
Otomian is a branch of the Oto-Manguean language family that comprises several closely related indigenous languages spoken in central Mexico.
-
B.
Osmanoğlu
Osmanoğlu is the surname borne by descendants of the Ottoman imperial dynasty, historically associated with the ruling house of the Ottoman Empire.
-
C.
Mahmut
Mahmut is a masculine given name commonly used in Turkish and related cultures, derived from the Arabic name Mahmoud.
-
D.
Gazi
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
-
E.
Gaziosmanpaşa
Gaziosmanpaşa is a densely populated residential and commercial district on the European side of Istanbul, known for its rapid urbanization and diverse working- and middle-class communities.
- 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_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7018fcbb48190a479f2effd939a8e |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89b05846c8190b49540aeae43dd9a |
completed | March 29, 2026, 3:22 a.m. |
| NEDg | Description generation | batch_69c89baadac081909921bb6215e79319 |
completed | March 29, 2026, 3:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c89c698f2c8190b5d2717835bd1d82 |
completed | March 29, 2026, 3:28 a.m. |
Created at: March 27, 2026, 3:59 p.m.