Triple
T7087291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Şerif Mardin |
E165107
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Şerif |
E254174
|
NE FINISHED |
How this triple was built (2 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: Şerif | Statement: [Şerif Mardin, givenName, Şerif]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Şerif Context triple: [Şerif Mardin, givenName, Şerif]
-
A.
Sherif
chosen
Sherif is a masculine given name of Arabic origin commonly used in Egypt and other Arabic-speaking countries.
-
B.
Sheriff
The Sheriff is the elected chief law enforcement official of a county, responsible for overseeing public safety, managing the sheriff’s office, and operating the county jail.
-
C.
Seriff
Seriff is the surname of Marc Seriff, an American computer scientist and co-founder of America Online (AOL).
-
D.
Sherriff’s Deputy
Sherriff’s Deputy is a Thoroughbred racehorse known for being sired by the stallion Curlin.
-
E.
Sheriff Calder
Sheriff Calder is the principled small-town lawman portrayed by Marlon Brando in the 1966 drama film "The Chase," known for trying to maintain order amid escalating violence and corruption.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e513d9b08190a8a8d213c2264ce4 |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c794888abc8190ada2ae826449745a |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:41 p.m.