Triple
T4469020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhu De |
E98448
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | De |
E98448
|
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: De | Statement: [Zhu De, hasGivenName, De]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: De Context triple: [Zhu De, hasGivenName, De]
-
A.
De
chosen
De is the given name of Zhu De, a prominent Chinese Communist military leader and one of the founders of the People’s Liberation Army.
-
B.
Den
Den is a Japanese surname borne by various notable figures in politics, industry, and the arts.
-
C.
Den
Den was a prominent pharaoh of Egypt’s First Dynasty, known for early administrative innovations and military campaigns that helped consolidate the young Egyptian state.
-
D.
DEN
DEN is the three-letter IATA airport code for Denver International Airport, the primary commercial airport serving Denver, Colorado.
-
E.
Des
Des is a given name, typically used as a shortened form of Desmond.
- 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_69b3454b4ae481908967426dd37284d6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3569cd03c8190927c596bedb45ac8 |
completed | March 13, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6286c75b08190bd683d300f6c97f0 |
completed | March 15, 2026, 3:33 a.m. |
Created at: March 12, 2026, 11:34 p.m.