Triple
T27770401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016–17 Serie A with Juventus FC |
E701727
|
entity |
| Predicate | defensiveRecord |
P172122
|
FINISHED |
| Object | best defence in Serie A 2016–17 |
—
|
LITERAL 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: best defence in Serie A 2016–17 | Statement: [2016–17 Serie A with Juventus FC, defensiveRecord, best defence in Serie A 2016–17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defensiveRecord Context triple: [2016–17 Serie A with Juventus FC, defensiveRecord, best defence in Serie A 2016–17]
-
A.
defensiveSuccess
Indicates that a defensive action successfully prevented or mitigated an opposing threat, attack, or adverse outcome.
-
B.
defensiveSide
Indicates which entity is acting in a defensive role or position relative to another entity or situation.
-
C.
defensiveRole
Indicates that an entity serves a protective or guarding function in relation to another entity or context.
-
D.
defensiveStructure
Indicates a relationship where one entity functions as a structure built or used to protect, defend, or fortify another entity or area.
-
E.
usedDefensiveLine
Indicates that an entity employed or deployed a particular defensive line as part of its strategy or actions.
- F. None of above. chosen
Provenance (4 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_69ef6a52fa708190934a32308d2c92dc |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8de0b948190ae333e9cd99cbf6c |
completed | May 3, 2026, 1:46 a.m. |
Created at: April 27, 2026, 4:34 p.m.