Triple
T12243275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Act III (Turandot) |
E291786
|
entity |
| Predicate | principalCharacter |
P9202
|
FINISHED |
| Object | Ping |
E291773
|
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: Ping | Statement: [Act III (Turandot), principalCharacter, Ping]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ping Context triple: [Act III (Turandot), principalCharacter, Ping]
-
A.
Ping
chosen
Ping is a comic yet poignant ministerial official in Giacomo Puccini’s opera "Turandot," known for his lyrical reflections on home and the burdens of courtly duty.
-
B.
Ping
Ping was the posthumous name of King Ping of Zhou, the Zhou dynasty ruler who moved the capital east to Luoyang, marking the beginning of the Eastern Zhou period in ancient China.
-
C.
Ping
Ping is the aunt of Meilin "Mei" Lee, a character from Disney and Pixar's animated film "Turning Red."
-
D.
Nping
Nping is a network packet generation and response analysis tool that comes bundled with the Nmap security scanner suite.
-
E.
Pingdom
Pingdom is a website and server monitoring service known for tracking uptime, performance, and user experience for online applications.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cb724448190be29fc1d2b946ab7 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e5ff68c81909d2796b24dd055f4 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:51 p.m.