Triple
T2630062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citytv |
E59609
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | City |
E201052
|
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: City | Statement: [Citytv, abbreviation, City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City Context triple: [Citytv, abbreviation, City]
-
A.
City
chosen
"City" is a classic science fiction fix-up novel by Clifford D. Simak, renowned for its poignant exploration of humanity’s decline and the rise of intelligent dogs in a far-future Earth.
-
B.
Urban
Urban is a common surname of various linguistic origins, notably borne by New Zealand actor Karl Urban.
-
C.
City Loop
City Loop is Melbourne’s central underground railway system that circulates suburban trains through key inner-city stations.
-
D.
المدينة
المدينة هي الاسم العربي المختصر لمدينة المدينة المنورة، إحدى أقدس المدن في الإسلام وثاني أقدس موقع بعد مكة المكرمة.
-
E.
Urban Jungle
Urban Jungle is a San Diego Zoo exhibit area featuring close-up encounters with giraffes and other savanna animals in an immersive, city-themed setting.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8c452508190b02e1630d725497a |
completed | March 7, 2026, 7:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af90a7021081909f81c4ddb48fa00c |
completed | March 10, 2026, 3:31 a.m. |
Created at: March 6, 2026, 9:50 p.m.