Triple
T7524064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma Su |
E177846
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Su |
E668074
|
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: Su | Statement: [Ma Su, givenName, Su]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Su Context triple: [Ma Su, givenName, Su]
-
A.
Su
Su is a skilled and deadly martial artist portrayed by Jet Li in the action film "Cradle 2 the Grave."
-
B.
Su
chosen
Su is the given name of Su Rogers, a British architect and academic known for her contributions to modern architecture and design education.
-
C.
Sus
Sus is a genus of mammals in the pig family that includes domestic pigs and several species of wild boar.
-
D.
Sy
Sy is a Diameter-based interface in telecommunications networks used for policy and charging control between the PCRF and online charging systems.
-
E.
SU
SU is the commonly used abbreviation for Stockholm University, a major public research university in Stockholm, Sweden.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c61b508190b582f54ecbb387e3 |
completed | March 27, 2026, 9:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84631e6bc819099b3a7819c3ae9a7 |
completed | March 28, 2026, 9:20 p.m. |
Created at: March 27, 2026, 3:46 p.m.