Triple
T4612591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westville |
E100792
|
entity |
| Predicate | hasStateAbbreviation |
P2461
|
FINISHED |
| Object | CT |
E63369
|
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: CT | Statement: [Westville, hasStateAbbreviation, CT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CT Context triple: [Westville, hasStateAbbreviation, CT]
-
A.
CT
CT is a 3GPP core network and terminals working group responsible for specifying protocols and interfaces for mobile telecommunications systems.
-
B.
CT
chosen
CT is the official two-letter United States Postal Service abbreviation for the state of Connecticut.
-
C.
CT
CT is the postcode area covering Canterbury and surrounding parts of east Kent in southeastern England.
-
D.
ECT
ECT is the three-letter station code used by Transport for London to identify Earl's Court Underground station.
-
E.
CT scanners
CT scanners are advanced medical imaging devices that use X-rays and computer processing to create detailed cross-sectional images of the body for diagnostic purposes.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59c11f5481909f61e23503711cf5 |
completed | March 20, 2026, 2:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfa895b7481909e54cfa56a54c8dc |
completed | March 21, 2026, 1:55 a.m. |
Created at: March 20, 2026, 1:12 p.m.