Triple
T15226000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Marks |
E363880
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Marks |
E87869
|
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: Marks | Statement: [David Marks, familyName, Marks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marks Context triple: [David Marks, familyName, Marks]
-
A.
Marks
chosen
Marks is a surname of English and Jewish origin borne by various notable individuals across fields such as sports, politics, and the arts.
-
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 the first name of Mark Cuban, the American billionaire entrepreneur and owner of the NBA’s Dallas Mavericks.
-
D.
Mark
The Mark was the basic unit of currency used in Germany during various historical periods, including the era of the Papiermark.
-
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.
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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078bb32881909927561c6c072546 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd379ac081909ebb3a18c2ee3b3c |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:12 a.m.