Triple
T19348008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Yellow Fairy Book |
E483933
|
entity |
| Predicate | hasLibraryOfCongressClassification |
P2387
|
FINISHED |
| Object |
PZ8
PZ8 is a Library of Congress Classification subclass that covers collections and adaptations of folk and fairy tales, myths, and legends in juvenile literature.
|
E1370998
|
NE FINISHED |
How this triple was built (4 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: PZ8 | Statement: [The Yellow Fairy Book, hasLibraryOfCongressClassification, PZ8]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PZ8 Context triple: [The Yellow Fairy Book, hasLibraryOfCongressClassification, PZ8]
-
A.
PZ
PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
-
B.
PZ
PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
-
C.
PZ
PZ is the IATA airline designator assigned to LATAM Airlines Paraguay, the Paraguayan branch of the LATAM Airlines Group.
-
D.
PZ
PZ is the commonly used abbreviation for Peshawar Zalmi, a professional cricket franchise that competes in the Pakistan Super League.
-
E.
PZ
PZ is the station code for Prinzregentenplatz, a Munich U-Bahn station on the city’s rapid transit network.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: PZ8 Triple: [The Yellow Fairy Book, hasLibraryOfCongressClassification, PZ8]
Generated description
PZ8 is a Library of Congress Classification subclass that covers collections and adaptations of folk and fairy tales, myths, and legends in juvenile literature.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PZ8 Target entity description: PZ8 is a Library of Congress Classification subclass that covers collections and adaptations of folk and fairy tales, myths, and legends in juvenile literature.
-
A.
PZ
PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
-
B.
PZ
PZ is the IATA airline designator assigned to LATAM Airlines Paraguay, the Paraguayan branch of the LATAM Airlines Group.
-
C.
PZ
PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
-
D.
PZ
PZ is the station code for Prinzregentenplatz, a Munich U-Bahn station on the city’s rapid transit network.
-
E.
PZ
PZ is the commonly used abbreviation for Peshawar Zalmi, a professional cricket franchise that competes in the Pakistan Super League.
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6185c95248190b1e5bb8626489767 |
completed | April 20, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a071bed1c608190a71094aa2645199d |
completed | May 15, 2026, 1:13 p.m. |
| NEDg | Description generation | batch_6a071cc1c76c8190b99ef2b319f6ab39 |
completed | May 15, 2026, 1:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a071d787dd881908d86c5fe52ca2561 |
completed | May 15, 2026, 1:19 p.m. |
Created at: April 10, 2026, 1:34 p.m.