Triple
T18901278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tower and the Hive series |
E462345
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Damia |
—
|
NE NERFINISHED |
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: Damia | Statement: [The Tower and the Hive series, hasPart, Damia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Damia Context triple: [The Tower and the Hive series, hasPart, Damia]
-
A.
Damia
chosen
Damia is a science fiction novel by Anne McCaffrey, part of her Tower and the Hive series that continues the story of powerful telepaths and their role in human and alien relations.
-
B.
Ariela
Ariela is a feminine given name, often considered a variant of Ariel, used in various cultures and languages.
-
C.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
D.
Melina
Melina is a key resistance fighter and love interest in the science fiction film "Total Recall," known for aiding the protagonist in his struggle against a corrupt Martian regime.
-
E.
Romina
Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c52954bc8190a237627c09615ac1 |
completed | April 20, 2026, 6:18 a.m. |
Created at: April 10, 2026, 11:58 a.m.