Triple
T28246375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hans Max Gamper-Haessig |
E712178
|
entity |
| Predicate | numberOfTermsAsPresidentOfFCBarcelona |
P80162
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Hans Max Gamper-Haessig, numberOfTermsAsPresidentOfFCBarcelona, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTermsAsPresidentOfFCBarcelona Context triple: [Hans Max Gamper-Haessig, numberOfTermsAsPresidentOfFCBarcelona, 5]
-
A.
numberOfTermsAsFCBarcelonaPresident
chosen
Indicates the number of separate terms an individual has served as president of FC Barcelona.
-
B.
presidencyPeriodAtFCBarcelona
Indicates the time span during which an individual served as president of FC Barcelona.
-
C.
managerYearsAtFCBarcelona
Indicates the number of years an individual served as a manager at FC Barcelona.
-
D.
termCountAsPresident
Indicates the number of terms an individual has served in the role of president.
-
E.
clubNumberAtBarcelona
Indicates the specific jersey number a player wore while playing for FC Barcelona.
- F. None of above.
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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ff4fc6077c8190b8fd9b43fcfde986 |
completed | May 9, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69ff4e61fb648190a72f7918961ece9c |
completed | May 9, 2026, 3:10 p.m. |
Created at: April 27, 2026, 11:01 p.m.