Triple
T9375094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Zombies |
E225627
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Tell Her No |
E794501
|
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: Tell Her No | Statement: [The Zombies, notableSong, Tell Her No]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tell Her No Context triple: [The Zombies, notableSong, Tell Her No]
-
A.
Tell Her No
chosen
"Tell Her No" is a 1965 hit single by the British rock band The Zombies, known for its distinctive minor-key melody and soulful vocal harmonies.
-
B.
Tell Me No
"Tell Me No" is a song by American singer Whitney Houston from her 2002 studio album "Just Whitney."
-
C.
Tell Her About It
"Tell Her About It" is a 1983 Motown-influenced pop song by Billy Joel that became a number-one hit on the Billboard Hot 100.
-
D.
The Good Girl
The Good Girl is a 2002 indie drama film starring Jennifer Aniston as a disillusioned small-town store clerk whose affair with a younger coworker upends her stagnant life.
-
E.
Las Mujeres Ya No Lloran
Las Mujeres Ya No Lloran is a studio album by Colombian singer Shakira that marks her return to music with a collection of songs about resilience, empowerment, and personal transformation.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca842d8ee88190aaaa639aa953185d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50a8b6f48190b77d93a172c54953 |
completed | April 1, 2026, 5:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d100d976d481909502901cec1fc83f |
completed | April 4, 2026, 12:15 p.m. |
Created at: March 30, 2026, 7:43 p.m.