Triple
T32093120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 British & Irish Lions tour to New Zealand |
E819647
|
entity |
| Predicate | firstTestCity |
P206179
|
FINISHED |
| Object | Auckland |
E18491
|
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: Auckland | Statement: [2017 British & Irish Lions tour to New Zealand, firstTestCity, Auckland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstTestCity Context triple: [2017 British & Irish Lions tour to New Zealand, firstTestCity, Auckland]
-
A.
firstSeasonCity
Indicates that a city is the location where a sports team played its first season.
-
B.
firstRaceCity
Indicates the city where an entity’s first race or competitive event took place.
-
C.
city1
Indicates that the subject is classified as a city.
-
D.
firstFinalCity
Indicates that a city is the final destination reached first in some ordered sequence of trips or routes.
-
E.
firstMatchCity
Indicates that the referenced city is the first one that matches a given set of criteria or search conditions among multiple possible cities.
- F. None of above. chosen
Provenance (5 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2f010442288190acf93d52cba859a6 |
completed | June 14, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 12:25 a.m.