Triple
T22721748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Wondolowski |
E561878
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object | Wondo |
—
|
NE NERFINISHED |
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: Wondo | Statement: [Chris Wondolowski, knownAs, Wondo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wondo Context triple: [Chris Wondolowski, knownAs, Wondo]
-
A.
Wondo
chosen
Wondo is the nickname of Chris Wondolowski, a prolific American soccer forward best known for his record-breaking goal-scoring career in Major League Soccer with the San Jose Earthquakes.
-
B.
Walungu
Walungu is a town in the eastern Democratic Republic of the Congo that serves as a local administrative and commercial hub.
-
C.
Etiwanda
Etiwanda is a historic former community in Southern California, now part of the city of Rancho Cucamonga, known for its early role in citrus agriculture and irrigation development.
-
D.
Datooga
Datooga is a Southern Nilotic language spoken primarily by the Datooga people of north-central Tanzania.
-
E.
Wandzia
Wandzia is a Polish diminutive form of the female given name Wanda, used as an affectionate or familiar nickname.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17926ae0c8190af8493cab6b15261 |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:20 p.m.