Triple
T11627024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Clinton |
E276296
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Mark |
unclear NED1
|
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: Mark | Statement: [Mark Clinton, hasGivenName, Mark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Context triple: [Mark Clinton, hasGivenName, Mark]
-
A.
Mark
The Mark was the basic unit of currency used in Germany during various historical periods, including the era of the Papiermark.
-
B.
Mark
Mark is a quirky, music-obsessed employee at the independent record store in the 1995 cult film "Empire Records," known for his goofy charm and laid-back attitude.
-
C.
Mark
Mark is a river in the southern Netherlands and northern Belgium that flows through the province of North Brabant before joining the Dintel.
-
D.
Mark
Mark is a punctuation symbol used in writing systems, including those that employ the Cyrillic Extended-B Unicode block.
-
E.
Mark
Mark is the introspective, emotionally detached young man who returns to his New Jersey hometown and undergoes a journey of self-discovery in the film "Garden State."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a1259cd08190a75eeacb5e39b858 |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee87845d588190bfa4197e7ab600a7 |
completed | April 26, 2026, 9:45 p.m. |
Created at: April 8, 2026, 9:39 p.m.